class_docstr: Bert Language model.
  Model returns [seq, batch, hidden] shape
class_docstr_tok: ["Bert","Language","model",".","Model","returns","[","seq",",","batch",",","hidden","]","shape"]
docstr: See megatron.model.transformer.set_input_tensor()
docstr_tok: ["See","megatron.model.transformer.set_input_tensor","(",")"]
code: def set_input_tensor(self, input_tensor):
      """See megatron.model.transformer.set_input_tensor()"""
      self.language_model.set_input_tensor(input_tensor)
  
file_path: NeMo/nemo/collections/nlp/models/language_modeling/megatron/bert_model.py
imports: import torch
  from nemo.collections.nlp.modules.common.megatron.language_model import get_language_model
  from nemo.collections.nlp.modules.common.megatron.module import MegatronModule
  from nemo.collections.nlp.modules.common.megatron.transformer import get_layer_norm
  from nemo.collections.nlp.modules.common.megatron.utils import ApexGuardDefaults, build_position_ids, erf_gelu, get_linear_layer, init_method_normal, openai_gelu, parallel_lm_logits, scaled_init_method_normal
label_desc: Use image node_id 2 for calling the BertModel obj's underlying member method code with example usage: obj.set_input_tensor(input_tensor) without return types